Sustainable Design of Smart Multimodal Urban Logistics in the Era of AI and Low-Altitude Economy

Conventionally, urban logistics operate in various independent transport modes, for example, trucks, vans, and motorcycles. Such operation will not be optimal when facing large-scale demand because isolated operation can be inefficient and environmental-unfriendly. To enhance the efficiency and sustainability of the next-generation urban logistics system, a comprehensive framework is proposed to identify the critical operation scenarios, its main system components, and the key technologies for applications of smart multimodal urban logistics (SMUL). There are four innovative characteristics in the proposed SMUL system: (1) co-modality for passenger and freight transportation through public transit; (2) integration of drone or unmanned aerial vehicles, autonomous delivery robots, automated delivery vehicles, and multimodal parcel lockers for last-mile delivery; (3) deployment and operation of robotic smart warehouses for storage; and (4) joint scheduling of various vehicles using large language model (LLM)-based agents. This paper focuses on two application cases, a last-mile home delivery service and a freight-integrated public transit service. A cyber-physical SMUL system is designed as the digital twin for monitoring the operations. A novel simulation platform is designed, using LLM-agents, for predicting system dynamics and thus supporting the economic evaluation of an SMUL system. Moreover, stakeholder benefit allocation and operation resilience are discussed for designing a sustainable SMUL system. Finally, insights are provided for policy and practice, for example, the logistics service providers are recommended to integrate aerial, road, and underground transport modes in consideration of local regulation, land use, and public trust in technology to achieve synergistic economic, social, and ecological efficiency.